Search Results for "perceptron c"

This is a small, self-contained framework for training and querying neural networks. Most notably, it contains a lightning-fast "fully fused" multi-layer perceptron (technical paper), a versatile multiresolution hash encoding (technical paper), as well as support for various other input encodings, losses, and optimizers. We provide a sample application where an image function (x,y) -> (R,G,B) is learned. The fully fused MLP component of this framework requires a very large amount of shared...

This project implements in C++ a bunch of known Neural Networks. So far the project implements: LVQ in several variants, SOM in several variants, Hopfield network and Perceptron. Other neural network types are planned, but not implemented yet. The project can run in two modes: command line tool and Python 7.2 extension. Currently, Python version appears more functional, as it allows easy interaction with algorithms developed by other people.

This project changes the MXNet code implementation in the original book "Learning Deep Learning by Hand" to TensorFlow2 implementation. After consulting Mr. Li Mu by the tutor of archersama , the implementation of this project has been agreed by Mr. Li Mu. Original authors: Aston Zhang, Li Mu, Zachary C. Lipton, Alexander J. Smola and other community contributors. There are some differences between the Chinese and English versions of this book . This project mainly focuses on TensorFlow2...

This projects aims at creating a simulator for the NARX (Nonlinear AutoRegressive with eXogenous inputs ) architecture with neural networks. The system can fallback to MLP ( multi layer perceptron ), TDNN ( time delay neural network ), BPTT ( backpropagation through time ) and a full NARX architecture. The system is intended to be used as a time series forecaster for educational purposes. This projects is my personal master thesis developed at the Master of Artificial Intelligence...

nunn is a collection of ML algorithms and related examples written in modern C++17.

This project includes the implementation of a neural network MLP, RBF, SOM and Hopfield networks in several popular programming languages. The project also includes examples of the use of neural networks as function approximation and time series prediction. Includes a special program makes it easy to test neural network based on training data and the optimization of the network.

A fast artificial intelligence library which currently supports: kNN (k-Nearest Neighbor algorithm) MLP (Multilayer-Perceptron)

Leark is a Data Mining library developed in C#.NET. It contains several methods for ranking web documents described with a set of normalized features, and a feature selection algorithm. The methods are based on perceptron and clustering.

Multi-Core optimized Perceptron Network is a high-performance artificial neural network specially designed for workstations with multi-core CPUs, implemented as a shared library and coded in C++.

MLP-Simulator is first of its kind Multi Layer Perceptron(MLP) Simulator developed using object-oriented methodology. This simulator can be embedded in any Intelligent System, that requires MLP for decision making, using standard API.

Neural network library for C++ applications in Windows and Linux. Multi-Layer perceptron, radial-basis function networks and Hopfield networks are supported. You can interface this with Matlab's Neural Network Toolbox using the Matlab Extensions Pack

mozg is a flexible, fast neurolibrary. It allows one to create, learn and use multi-layer perceptron (MLP), which is the most popular artificial neural network (ANN). This work is based on library originally written by Alexy Filin.